MCP-Pipeline/MCPStack

Stack & Orchestrate MCP Tools — The Scikit-Learn-Pipeline Way , For LLMs

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/ 100
Emerging

This tool helps you combine and manage different AI capabilities, called Model Context Protocols (MCPs), for your Large Language Models (LLMs). You can chain together various MCPs to create a customized workflow, specifying exactly what functions your LLM can access. This is ideal for AI product developers or researchers who want precise control over how their LLMs interact with external tools and data.

No commits in the last 6 months. Available on PyPI.

Use this if you need to orchestrate specific tools and datasets for your Large Language Models, similar to how scikit-learn pipelines manage data processing and machine learning models.

Not ideal if you are a casual LLM user looking for a simple, out-of-the-box solution without needing to customize tool interactions or develop new MCPs.

LLM orchestration AI toolchaining prompt engineering AI workflow management model interaction control
Stale 6m
Maintenance 2 / 25
Adoption 6 / 25
Maturity 24 / 25
Community 15 / 25

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Stars

16

Forks

4

Language

Python

License

MIT

Last pushed

Sep 20, 2025

Commits (30d)

0

Dependencies

10

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